Triple

T15895884
Position Surface form Disambiguated ID Type / Status
Subject Rometty E385450 entity
Predicate usedBy P260 FINISHED
Object Ginni Rometty E81371 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ginni Rometty | Statement: [Rometty, usedBy, Ginni Rometty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ginni Rometty
Context triple: [Rometty, usedBy, Ginni Rometty]
  • A. Ginni Rometty chosen
    Ginni Rometty is an American business executive best known for serving as the first female CEO of IBM, where she led the company’s strategic shift toward cloud computing and artificial intelligence.
  • B. Anne Mulcahy
    Anne Mulcahy is an American business executive best known for leading Xerox Corporation’s turnaround as its CEO and chairwoman in the early 2000s.
  • C. Mark Anthony Rometty
    Mark Anthony Rometty is the husband of former IBM CEO Ginni Rometty and is known primarily in connection with her public and professional life.
  • D. Meg Whitman
    Meg Whitman is an American business executive best known for leading eBay’s rapid growth as CEO and later serving as CEO of Hewlett Packard Enterprise and U.S. Ambassador to Kenya.
  • E. Patty McCord
    Patty McCord is a human resources executive and author best known as Netflix’s former Chief Talent Officer and co-creator of its influential “culture deck” on freedom and responsibility.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15638f5bc81908de13f4b6a52b60c completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb04b55ec8190a5b3513b2afa4f83 completed May 9, 2026, 10:08 p.m.
Created at: April 10, 2026, 4:51 a.m.